Overview

Dataset statistics

Number of variables40
Number of observations1260
Missing cells25840
Missing cells (%)51.3%
Total size in memory393.9 KiB
Average record size in memory320.1 B

Variable types

Text34
Numeric6

Alerts

dedicated_power_plant has constant value "2.0"Constant
number_of_generators has constant value "0.0"Constant
address has 67 (5.3%) missing valuesMissing
zip has 35 (2.8%) missing valuesMissing
purpose has 1228 (97.5%) missing valuesMissing
operator has 599 (47.5%) missing valuesMissing
tenant has 1243 (98.7%) missing valuesMissing
info_source_1 has 121 (9.6%) missing valuesMissing
info_source_2 has 741 (58.8%) missing valuesMissing
info_source_3 has 1110 (88.1%) missing valuesMissing
info_source_4 has 1196 (94.9%) missing valuesMissing
info_source_5 has 1223 (97.1%) missing valuesMissing
info_source_6 has 1235 (98.0%) missing valuesMissing
info_source_7 has 1249 (99.1%) missing valuesMissing
info_source_8 has 1255 (99.6%) missing valuesMissing
date_updated has 102 (8.1%) missing valuesMissing
mw_high has 857 (68.0%) missing valuesMissing
power_source has 1230 (97.6%) missing valuesMissing
dedicated_power_plant has 1259 (99.9%) missing valuesMissing
number_of_generators has 1259 (99.9%) missing valuesMissing
number_of_buildings has 1183 (93.9%) missing valuesMissing
cooling_source has 1241 (98.5%) missing valuesMissing
facility_size_sq_ft has 474 (37.6%) missing valuesMissing
cooling_type has 1244 (98.7%) missing valuesMissing
property_size_acres has 575 (45.6%) missing valuesMissing
project_cost has 1088 (86.3%) missing valuesMissing
other_info has 807 (64.0%) missing valuesMissing
status_detail has 1198 (95.1%) missing valuesMissing
expected_date_online has 1224 (97.1%) missing valuesMissing
county has 771 (61.2%) missing valuesMissing
facility_id has unique valuesUnique

Reproduction

Analysis started2026-01-10 22:20:04.584577
Analysis finished2026-01-10 22:20:05.603856
Duration1.02 second
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

facility_id
Text

Unique 

Distinct1260
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:06.345562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length18
Median length3
Mean length4.842063492
Min length1

Characters and Unicode

Total characters6101
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1260 ?
Unique (%)100.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
11
 
0.1%
21
 
0.1%
31
 
0.1%
41
 
0.1%
51
 
0.1%
61
 
0.1%
1764304493710-22581
 
0.1%
71
 
0.1%
81
 
0.1%
91
 
0.1%
Other values (1250)1250
99.2%
2026-01-10T17:20:07.143993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1843
13.8%
7698
11.4%
6690
11.3%
3594
9.7%
5555
9.1%
9538
8.8%
4535
8.8%
2502
8.2%
8501
8.2%
0491
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)6101
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1843
13.8%
7698
11.4%
6690
11.3%
3594
9.7%
5555
9.1%
9538
8.8%
4535
8.8%
2502
8.2%
8501
8.2%
0491
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)6101
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1843
13.8%
7698
11.4%
6690
11.3%
3594
9.7%
5555
9.1%
9538
8.8%
4535
8.8%
2502
8.2%
8501
8.2%
0491
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)6101
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1843
13.8%
7698
11.4%
6690
11.3%
3594
9.7%
5555
9.1%
9538
8.8%
4535
8.8%
2502
8.2%
8501
8.2%
0491
8.0%

name
Text

Distinct1090
Distinct (%)86.7%
Missing3
Missing (%)0.2%
Memory size10.0 KiB
2026-01-10T17:20:07.590919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length74
Median length53
Mean length22.30708035
Min length2

Characters and Unicode

Total characters28040
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1034 ?
Unique (%)82.3%

Sample

1st rowLogistic Land Investments LLC developer
2nd rowDC Blox
3rd rowGoogle data center
4th rowDC Blox
5th rowMeta Data Center
ValueCountFrequency (%)
data507
 
11.7%
center479
 
11.1%
project97
 
2.2%
llc84
 
1.9%
campus61
 
1.4%
digital55
 
1.3%
park52
 
1.2%
amazon42
 
1.0%
microsoft42
 
1.0%
atlanta41
 
0.9%
Other values (1381)2872
66.3%
2026-01-10T17:20:08.349741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3083
 
11.0%
e2368
 
8.4%
a2192
 
7.8%
t2017
 
7.2%
r1487
 
5.3%
n1427
 
5.1%
o1136
 
4.1%
i918
 
3.3%
C891
 
3.2%
l770
 
2.7%
Other values (71)11751
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)28040
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3083
 
11.0%
e2368
 
8.4%
a2192
 
7.8%
t2017
 
7.2%
r1487
 
5.3%
n1427
 
5.1%
o1136
 
4.1%
i918
 
3.3%
C891
 
3.2%
l770
 
2.7%
Other values (71)11751
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)28040
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3083
 
11.0%
e2368
 
8.4%
a2192
 
7.8%
t2017
 
7.2%
r1487
 
5.3%
n1427
 
5.1%
o1136
 
4.1%
i918
 
3.3%
C891
 
3.2%
l770
 
2.7%
Other values (71)11751
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)28040
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3083
 
11.0%
e2368
 
8.4%
a2192
 
7.8%
t2017
 
7.2%
r1487
 
5.3%
n1427
 
5.1%
o1136
 
4.1%
i918
 
3.3%
C891
 
3.2%
l770
 
2.7%
Other values (71)11751
41.9%

address
Text

Missing 

Distinct1181
Distinct (%)99.0%
Missing67
Missing (%)5.3%
Memory size10.0 KiB
2026-01-10T17:20:08.914375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length155
Median length68
Mean length20.83822297
Min length5

Characters and Unicode

Total characters24860
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1173 ?
Unique (%)98.3%

Sample

1st rowRock Mountain Lake Rd
2nd row433 6th St S
3rd row48809 Alabama 277
4th row333 Diamond Dr NW
5th row5400 Prosperity Dr NW
ValueCountFrequency (%)
rd338
 
7.2%
dr171
 
3.6%
and90
 
1.9%
blvd85
 
1.8%
road83
 
1.8%
st79
 
1.7%
of65
 
1.4%
ave59
 
1.3%
hwy55
 
1.2%
near45
 
1.0%
Other values (1964)3639
77.3%
2026-01-10T17:20:09.803846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3517
 
14.1%
e1213
 
4.9%
a966
 
3.9%
r921
 
3.7%
t903
 
3.6%
0891
 
3.6%
R877
 
3.5%
o850
 
3.4%
n847
 
3.4%
1785
 
3.2%
Other values (67)13090
52.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)24860
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3517
 
14.1%
e1213
 
4.9%
a966
 
3.9%
r921
 
3.7%
t903
 
3.6%
0891
 
3.6%
R877
 
3.5%
o850
 
3.4%
n847
 
3.4%
1785
 
3.2%
Other values (67)13090
52.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)24860
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3517
 
14.1%
e1213
 
4.9%
a966
 
3.9%
r921
 
3.7%
t903
 
3.6%
0891
 
3.6%
R877
 
3.5%
o850
 
3.4%
n847
 
3.4%
1785
 
3.2%
Other values (67)13090
52.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)24860
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3517
 
14.1%
e1213
 
4.9%
a966
 
3.9%
r921
 
3.7%
t903
 
3.6%
0891
 
3.6%
R877
 
3.5%
o850
 
3.4%
n847
 
3.4%
1785
 
3.2%
Other values (67)13090
52.7%

city
Text

Distinct565
Distinct (%)45.1%
Missing6
Missing (%)0.5%
Memory size10.0 KiB
2026-01-10T17:20:10.309669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length35
Median length32
Mean length8.994417863
Min length4

Characters and Unicode

Total characters11279
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique397 ?
Unique (%)31.7%

Sample

1st rowBessemer
2nd rowBirmingham
3rd rowBridgeport
4th rowHuntsville
5th rowHuntsville
ValueCountFrequency (%)
sterling82
 
5.3%
ashburn69
 
4.4%
manassas62
 
4.0%
atlanta49
 
3.1%
san26
 
1.7%
antonio22
 
1.4%
leesburg19
 
1.2%
city19
 
1.2%
new17
 
1.1%
springs17
 
1.1%
Other values (579)1177
75.5%
2026-01-10T17:20:10.975741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a980
 
8.7%
n965
 
8.6%
e909
 
8.1%
l749
 
6.6%
s718
 
6.4%
r713
 
6.3%
i676
 
6.0%
t639
 
5.7%
o619
 
5.5%
u328
 
2.9%
Other values (47)3983
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)11279
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a980
 
8.7%
n965
 
8.6%
e909
 
8.1%
l749
 
6.6%
s718
 
6.4%
r713
 
6.3%
i676
 
6.0%
t639
 
5.7%
o619
 
5.5%
u328
 
2.9%
Other values (47)3983
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)11279
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a980
 
8.7%
n965
 
8.6%
e909
 
8.1%
l749
 
6.6%
s718
 
6.4%
r713
 
6.3%
i676
 
6.0%
t639
 
5.7%
o619
 
5.5%
u328
 
2.9%
Other values (47)3983
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)11279
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a980
 
8.7%
n965
 
8.6%
e909
 
8.1%
l749
 
6.6%
s718
 
6.4%
r713
 
6.3%
i676
 
6.0%
t639
 
5.7%
o619
 
5.5%
u328
 
2.9%
Other values (47)3983
35.3%

state
Text

Distinct45
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:11.201636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2520
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rowAL
2nd rowAL
3rd rowAL
4th rowAL
5th rowAL
ValueCountFrequency (%)
va443
35.2%
ga165
 
13.1%
tx139
 
11.0%
pa84
 
6.7%
oh43
 
3.4%
in34
 
2.7%
az25
 
2.0%
ny25
 
2.0%
mi20
 
1.6%
il20
 
1.6%
Other values (35)262
20.8%
2026-01-10T17:20:11.603068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A782
31.0%
V462
18.3%
G165
 
6.5%
T157
 
6.2%
X139
 
5.5%
N135
 
5.4%
I106
 
4.2%
O88
 
3.5%
P84
 
3.3%
M70
 
2.8%
Other values (14)332
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)2520
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A782
31.0%
V462
18.3%
G165
 
6.5%
T157
 
6.2%
X139
 
5.5%
N135
 
5.4%
I106
 
4.2%
O88
 
3.5%
P84
 
3.3%
M70
 
2.8%
Other values (14)332
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2520
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A782
31.0%
V462
18.3%
G165
 
6.5%
T157
 
6.2%
X139
 
5.5%
N135
 
5.4%
I106
 
4.2%
O88
 
3.5%
P84
 
3.3%
M70
 
2.8%
Other values (14)332
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2520
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A782
31.0%
V462
18.3%
G165
 
6.5%
T157
 
6.2%
X139
 
5.5%
N135
 
5.4%
I106
 
4.2%
O88
 
3.5%
P84
 
3.3%
M70
 
2.8%
Other values (14)332
13.2%

zip
Real number (ℝ)

Missing 

Distinct637
Distinct (%)52.0%
Missing35
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean39215.89143
Minimum2155
Maximum99354
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:11.857382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2155
5-th percentile15805.4
Q120166
median30014
Q355024
95-th percentile86890.8
Maximum99354
Range97199
Interquartile range (IQR)34858

Descriptive statistics

Standard deviation24850.72775
Coefficient of variation (CV)0.6336902424
Kurtosis-0.4859999667
Mean39215.89143
Median Absolute Deviation (MAD)9904
Skewness0.962854467
Sum48039467
Variance617558669.6
MonotonicityNot monotonic
2026-01-10T17:20:12.136953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2016691
 
7.2%
2014761
 
4.8%
2010940
 
3.2%
2011020
 
1.6%
3012217
 
1.3%
2017516
 
1.3%
3030315
 
1.2%
7825113
 
1.0%
2254612
 
1.0%
2015511
 
0.9%
Other values (627)929
73.7%
(Missing)35
 
2.8%
ValueCountFrequency (%)
21551
0.1%
42401
0.1%
45781
0.1%
60021
0.1%
63341
0.1%
ValueCountFrequency (%)
993541
 
0.1%
990191
 
0.1%
988483
0.2%
988371
 
0.1%
988281
 
0.1%
Distinct3
Distinct (%)0.2%
Missing6
Missing (%)0.5%
Memory size10.0 KiB
2026-01-10T17:20:12.350749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.27830941
Min length3

Characters and Unicode

Total characters5365
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHigh
2nd rowHigh
3rd rowHigh
4th rowHigh
5th rowHigh
ValueCountFrequency (%)
high1015
80.9%
medium196
 
15.6%
low43
 
3.4%
2026-01-10T17:20:12.678548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i1211
22.6%
H1015
18.9%
g1015
18.9%
h1015
18.9%
M196
 
3.7%
e196
 
3.7%
d196
 
3.7%
u196
 
3.7%
m196
 
3.7%
L43
 
0.8%
Other values (2)86
 
1.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)5365
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i1211
22.6%
H1015
18.9%
g1015
18.9%
h1015
18.9%
M196
 
3.7%
e196
 
3.7%
d196
 
3.7%
u196
 
3.7%
m196
 
3.7%
L43
 
0.8%
Other values (2)86
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)5365
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i1211
22.6%
H1015
18.9%
g1015
18.9%
h1015
18.9%
M196
 
3.7%
e196
 
3.7%
d196
 
3.7%
u196
 
3.7%
m196
 
3.7%
L43
 
0.8%
Other values (2)86
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)5365
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i1211
22.6%
H1015
18.9%
g1015
18.9%
h1015
18.9%
M196
 
3.7%
e196
 
3.7%
d196
 
3.7%
u196
 
3.7%
m196
 
3.7%
L43
 
0.8%
Other values (2)86
 
1.6%

purpose
Text

Missing 

Distinct7
Distinct (%)21.9%
Missing1228
Missing (%)97.5%
Memory size10.0 KiB
2026-01-10T17:20:12.839275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length27
Median length2
Mean length6.25
Min length2

Characters and Unicode

Total characters200
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)15.6%

Sample

1st rowAI/cloud-computing
2nd rowAI
3rd rowAI "superfactory"
4th rowAI
5th rowTelecommunication routing
ValueCountFrequency (%)
ai30
66.7%
bitcoin3
 
6.7%
transitioning2
 
4.4%
to2
 
4.4%
and2
 
4.4%
superfactory1
 
2.2%
ai/cloud-computing1
 
2.2%
telecommunication1
 
2.2%
routing1
 
2.2%
cloud1
 
2.2%
2026-01-10T17:20:13.206503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A31
15.5%
I31
15.5%
i17
8.5%
n16
 
8.0%
o15
 
7.5%
t14
 
7.0%
13
 
6.5%
c8
 
4.0%
u7
 
3.5%
a6
 
3.0%
Other values (16)42
21.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)200
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A31
15.5%
I31
15.5%
i17
8.5%
n16
 
8.0%
o15
 
7.5%
t14
 
7.0%
13
 
6.5%
c8
 
4.0%
u7
 
3.5%
a6
 
3.0%
Other values (16)42
21.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)200
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A31
15.5%
I31
15.5%
i17
8.5%
n16
 
8.0%
o15
 
7.5%
t14
 
7.0%
13
 
6.5%
c8
 
4.0%
u7
 
3.5%
a6
 
3.0%
Other values (16)42
21.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)200
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A31
15.5%
I31
15.5%
i17
8.5%
n16
 
8.0%
o15
 
7.5%
t14
 
7.0%
13
 
6.5%
c8
 
4.0%
u7
 
3.5%
a6
 
3.0%
Other values (16)42
21.0%

operator
Text

Missing 

Distinct353
Distinct (%)53.4%
Missing599
Missing (%)47.5%
Memory size10.0 KiB
2026-01-10T17:20:13.674565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length116
Median length55
Mean length17.36459909
Min length2

Characters and Unicode

Total characters11478
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)43.4%

Sample

1st rowGoogle
2nd rowMeta
3rd rowMeta
4th rowGoogle
5th rowMicrosoft
ValueCountFrequency (%)
llc182
 
10.2%
data91
 
5.1%
amazon74
 
4.1%
inc56
 
3.1%
microsoft55
 
3.1%
services43
 
2.4%
centers39
 
2.2%
google30
 
1.7%
digital30
 
1.7%
qts24
 
1.3%
Other values (540)1164
65.1%
2026-01-10T17:20:14.458706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1127
 
9.8%
e578
 
5.0%
L549
 
4.8%
C543
 
4.7%
a535
 
4.7%
o513
 
4.5%
t459
 
4.0%
A431
 
3.8%
n423
 
3.7%
r396
 
3.5%
Other values (65)5924
51.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)11478
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1127
 
9.8%
e578
 
5.0%
L549
 
4.8%
C543
 
4.7%
a535
 
4.7%
o513
 
4.5%
t459
 
4.0%
A431
 
3.8%
n423
 
3.7%
r396
 
3.5%
Other values (65)5924
51.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)11478
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1127
 
9.8%
e578
 
5.0%
L549
 
4.8%
C543
 
4.7%
a535
 
4.7%
o513
 
4.5%
t459
 
4.0%
A431
 
3.8%
n423
 
3.7%
r396
 
3.5%
Other values (65)5924
51.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)11478
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1127
 
9.8%
e578
 
5.0%
L549
 
4.8%
C543
 
4.7%
a535
 
4.7%
o513
 
4.5%
t459
 
4.0%
A431
 
3.8%
n423
 
3.7%
r396
 
3.5%
Other values (65)5924
51.6%

tenant
Text

Missing 

Distinct11
Distinct (%)64.7%
Missing1243
Missing (%)98.7%
Memory size10.0 KiB
2026-01-10T17:20:14.673712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length18
Mean length11.23529412
Min length3

Characters and Unicode

Total characters191
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)41.2%

Sample

1st rowMicrosoft
2nd rowMeta
3rd rowGail Technology
4th rowAWS
5th rowAnthropic
ValueCountFrequency (%)
coreweave4
14.3%
meta3
10.7%
google3
10.7%
ai2
 
7.1%
open2
 
7.1%
oracle2
 
7.1%
and2
 
7.1%
anthropic2
 
7.1%
fluidstack2
 
7.1%
microsoft1
 
3.6%
Other values (5)5
17.9%
2026-01-10T17:20:15.123863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e24
 
12.6%
o17
 
8.9%
a15
 
7.9%
l11
 
5.8%
11
 
5.8%
r10
 
5.2%
t8
 
4.2%
c8
 
4.2%
i7
 
3.7%
n7
 
3.7%
Other values (24)73
38.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)191
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e24
 
12.6%
o17
 
8.9%
a15
 
7.9%
l11
 
5.8%
11
 
5.8%
r10
 
5.2%
t8
 
4.2%
c8
 
4.2%
i7
 
3.7%
n7
 
3.7%
Other values (24)73
38.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)191
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e24
 
12.6%
o17
 
8.9%
a15
 
7.9%
l11
 
5.8%
11
 
5.8%
r10
 
5.2%
t8
 
4.2%
c8
 
4.2%
i7
 
3.7%
n7
 
3.7%
Other values (24)73
38.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)191
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e24
 
12.6%
o17
 
8.9%
a15
 
7.9%
l11
 
5.8%
11
 
5.8%
r10
 
5.2%
t8
 
4.2%
c8
 
4.2%
i7
 
3.7%
n7
 
3.7%
Other values (24)73
38.2%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:15.325616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length29
Mean length21.52063492
Min length13

Characters and Unicode

Total characters27116
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGoogle Maps and other sources
2nd rowGoogle Maps only
3rd rowGoogle Maps and other sources
4th rowGoogle Maps only
5th rowGoogle Maps and other sources
ValueCountFrequency (%)
sources1196
26.2%
other1196
26.2%
maps723
15.9%
google723
15.9%
and659
14.4%
only64
 
1.4%
2026-01-10T17:20:15.741961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o3365
12.4%
3301
12.2%
e3115
11.5%
s3115
11.5%
r2392
8.8%
a1382
 
5.1%
u1196
 
4.4%
c1196
 
4.4%
h1196
 
4.4%
t1196
 
4.4%
Other values (9)5662
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)27116
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o3365
12.4%
3301
12.2%
e3115
11.5%
s3115
11.5%
r2392
8.8%
a1382
 
5.1%
u1196
 
4.4%
c1196
 
4.4%
h1196
 
4.4%
t1196
 
4.4%
Other values (9)5662
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)27116
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o3365
12.4%
3301
12.2%
e3115
11.5%
s3115
11.5%
r2392
8.8%
a1382
 
5.1%
u1196
 
4.4%
c1196
 
4.4%
h1196
 
4.4%
t1196
 
4.4%
Other values (9)5662
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)27116
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o3365
12.4%
3301
12.2%
e3115
11.5%
s3115
11.5%
r2392
8.8%
a1382
 
5.1%
u1196
 
4.4%
c1196
 
4.4%
h1196
 
4.4%
t1196
 
4.4%
Other values (9)5662
20.9%

info_source_1
Text

Missing 

Distinct955
Distinct (%)83.8%
Missing121
Missing (%)9.6%
Memory size10.0 KiB
2026-01-10T17:20:16.137983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length539
Median length165
Mean length105.4407375
Min length21

Characters and Unicode

Total characters120097
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique867 ?
Unique (%)76.1%

Sample

1st rowhttps://www.datacenterdynamics.com/en/news/700-acre-data-center-in-bessemer-alabama-approved-despite-opposition/
2nd rowhttps://www.madeinalabama.com/2018/04/google-kicks-off-construction-on-alabama-data-center/
3rd rowhttps://www.datacenterdynamics.com/en/news/meta-to-build-800m-data-center-in-montgomery-alabama/
4th rowhttps://www.datacenterdynamics.com/en/news/meta-to-build-800m-data-center-in-montgomery-alabama/
5th rowhttps://www.datacenterdynamics.com/en/news/serverfarm-targets-135-acre-data-center-campus-in-arkansas/
ValueCountFrequency (%)
https://gis-tceq.opendata.arcgis.com/datasets/daece6e3181140f69093ab69cf9ae0ba/explore?layer=0&showtable=true14
 
1.2%
https://www.fairfaxcounty.gov/planning-development/sites/planning-development/files/assets/documents/pdf/data-centers-report.pdf#page=112
 
1.0%
https://www.datacenterdynamics.com/en/news/cielo-digital-infrastructure-plans-300mw-data-center-campus-in-south-carolina10
 
0.8%
https://comptroller.texas.gov/taxes/data-centers/data-center-lists.php7
 
0.6%
https://invest.jll.com/us/en/listings/special-purpose-facility/8-asset-switch-portfolio7
 
0.6%
https://www.datacenterdynamics.com/en/news/soluna-to-develop-two-new-data-centers-in-texas-with-a-combined-capacity-of-350mw7
 
0.6%
https://www.datacenterdynamics.com/en/news/aligned-stream-and-nexstar-planning-data-center-campuses-in-elk-grove-area-of-chicago7
 
0.6%
https://8888cre.com/data-center-land-for-sale-in-tax-incentive-zone-data-center-land-for-sale-with-power-substation-access-megawatt-powerline-near-dallas-texas-fort-worth-tx.pdf6
 
0.5%
https://hillsboroherald.com/flexentials-new-hillsboro-6-data-center-marks-a-shift-from-jobs-to-joules6
 
0.5%
https://www.datacenterdynamics.com/en/news/microsoft-files-for-new-data-center-campus-in-des-moines-iowa6
 
0.5%
Other values (978)1105
93.1%
2026-01-10T17:20:16.813778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e9454
 
7.9%
t9039
 
7.5%
a8652
 
7.2%
-7647
 
6.4%
n6805
 
5.7%
/6353
 
5.3%
s6163
 
5.1%
o5707
 
4.8%
c5284
 
4.4%
r5197
 
4.3%
Other values (70)49796
41.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)120097
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e9454
 
7.9%
t9039
 
7.5%
a8652
 
7.2%
-7647
 
6.4%
n6805
 
5.7%
/6353
 
5.3%
s6163
 
5.1%
o5707
 
4.8%
c5284
 
4.4%
r5197
 
4.3%
Other values (70)49796
41.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)120097
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e9454
 
7.9%
t9039
 
7.5%
a8652
 
7.2%
-7647
 
6.4%
n6805
 
5.7%
/6353
 
5.3%
s6163
 
5.1%
o5707
 
4.8%
c5284
 
4.4%
r5197
 
4.3%
Other values (70)49796
41.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)120097
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e9454
 
7.9%
t9039
 
7.5%
a8652
 
7.2%
-7647
 
6.4%
n6805
 
5.7%
/6353
 
5.3%
s6163
 
5.1%
o5707
 
4.8%
c5284
 
4.4%
r5197
 
4.3%
Other values (70)49796
41.5%

info_source_2
Text

Missing 

Distinct490
Distinct (%)94.4%
Missing741
Missing (%)58.8%
Memory size10.0 KiB
2026-01-10T17:20:17.158685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length539
Median length161
Mean length106.4643545
Min length26

Characters and Unicode

Total characters55255
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique472 ?
Unique (%)90.9%

Sample

1st rowhttps://www.youtube.com/watch?v=ICSrvQ7meow&ab_channel=InsideClimateNews
2nd rowhttps://claycorp.com/work/mission-critical
3rd rowhttps://rbnenergy.com/i-know-places-tech-giants-may-be-the-surest-bets-for-data-center-power-demand
4th rowhttps://www.fox10phoenix.com/news/10b-data-center-plan-page-area-faces-pushback-from-residents
5th rowhttps://www.tract.com/news/tract-closes-acquisition-of-2069-acres-in-buckeye-arizona/
ValueCountFrequency (%)
https://rbnenergy.com/i-know-places-tech-giants-may-be-the-surest-bets-for-data-center-power-demand8
 
1.5%
https://qtsdatacenters.com/data-centers/atlanta-14
 
0.8%
https://bitfarms.com/our-portfolio/data-centers/north-america4
 
0.8%
https://www.dispatch.com/story/business/2025/04/07/microsoft-backs-out-of-plans-to-build-data-centers-in-licking-county/829730970073
 
0.6%
https://www.wfmj.com/story/53109325/lordstown-part-of-mammoth-dollar500-billion-artificial-intelligence-data-center-project2
 
0.4%
https://www.citizensvoice.com/2025/08/11/senate-data-center-hearing-at-valley-view-largely-touts-benefits2
 
0.4%
https://www.edged.us/atlanta2
 
0.4%
https://www.datacenterwatch.org/report2
 
0.4%
https://qtsdatacenters.com/data-centers/suwanee-12
 
0.4%
https://www.datacenterdynamics.com/en/news/dc-blox-secures-115bn-green-loan-for-atlanta-data-center-development2
 
0.4%
Other values (480)488
94.0%
2026-01-10T17:20:17.848155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t4114
 
7.4%
e3968
 
7.2%
a3832
 
6.9%
s2737
 
5.0%
/2727
 
4.9%
o2677
 
4.8%
r2632
 
4.8%
-2433
 
4.4%
n2426
 
4.4%
p2206
 
4.0%
Other values (67)25503
46.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)55255
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t4114
 
7.4%
e3968
 
7.2%
a3832
 
6.9%
s2737
 
5.0%
/2727
 
4.9%
o2677
 
4.8%
r2632
 
4.8%
-2433
 
4.4%
n2426
 
4.4%
p2206
 
4.0%
Other values (67)25503
46.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)55255
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t4114
 
7.4%
e3968
 
7.2%
a3832
 
6.9%
s2737
 
5.0%
/2727
 
4.9%
o2677
 
4.8%
r2632
 
4.8%
-2433
 
4.4%
n2426
 
4.4%
p2206
 
4.0%
Other values (67)25503
46.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)55255
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t4114
 
7.4%
e3968
 
7.2%
a3832
 
6.9%
s2737
 
5.0%
/2727
 
4.9%
o2677
 
4.8%
r2632
 
4.8%
-2433
 
4.4%
n2426
 
4.4%
p2206
 
4.0%
Other values (67)25503
46.2%

info_source_3
Text

Missing 

Distinct148
Distinct (%)98.7%
Missing1110
Missing (%)88.1%
Memory size10.0 KiB
2026-01-10T17:20:18.144655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length242
Median length132
Mean length110.9133333
Min length29

Characters and Unicode

Total characters16637
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)97.3%

Sample

1st rowhttps://www.al.com/news/2025/06/14-billion-proposed-data-center-near-birmingham-hits-another-hurdle.html
2nd rowhttps://www.arkansasedc.com/news-events/newsroom/detail/2025/10/02/google-locating-new-data-center-in-west-memphis--arkansas-with-multi-billion-dollar-investment
3rd rowhttps://lakepowellchronicle.com/stories/international-development-company-proposes-10-billion-data-center-for-page,78901
4th rowhttps://azbigmedia.com/business/33-billion-data-center-industrial-park-coming-to-pinal-county/
5th rowhttps://www.foxbusiness.com/economy/arizona-city-defeats-massive-data-center-project-over-water-energy-concerns
ValueCountFrequency (%)
https://www.thetimes-tribune.com/2025/05/18/data-centers-could-reshape-landscape-in-nepa2
 
1.3%
https://www.fox43.com/article/news/local/york-county/500-million-data-center-fairview-township-york-county/521-81526e0c-e19d-4211-adaf-d2cee8ecda8f2
 
1.3%
https://www.al.com/news/2025/06/14-billion-proposed-data-center-near-birmingham-hits-another-hurdle.html1
 
0.7%
https://www.arkansasedc.com/news-events/newsroom/detail/2025/10/02/google-locating-new-data-center-in-west-memphis--arkansas-with-multi-billion-dollar-investment1
 
0.7%
https://www.foxbusiness.com/economy/arizona-city-defeats-massive-data-center-project-over-water-energy-concerns1
 
0.7%
https://www.coresite.com/news/coresite-achieves-key-construction-milestone-for-new-de3-data-center-in-denver1
 
0.7%
https://www.ajc.com/news/2025/06/as-data-centers-grow-larger-so-does-pushback-across-georgia1
 
0.7%
https://www.datacenterdynamics.com/en/news/digital-realty-files-to-develop-two-building-campus-outside-atlanta-georgia1
 
0.7%
https://www.earlycountynews.com/articles/qts-data-centers-considers-a-location-in-blakely1
 
0.7%
https://www.ajc.com/news/business/19b-data-center-campus-proposed-northwest-of-atlanta/fpmrpjcyergxlland6izacsvem1
 
0.7%
Other values (138)138
92.0%
2026-01-10T17:20:18.747404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
-1299
 
7.8%
e1265
 
7.6%
t1225
 
7.4%
a1099
 
6.6%
n1002
 
6.0%
o896
 
5.4%
s891
 
5.4%
/888
 
5.3%
r736
 
4.4%
i703
 
4.2%
Other values (64)6633
39.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)16637
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
-1299
 
7.8%
e1265
 
7.6%
t1225
 
7.4%
a1099
 
6.6%
n1002
 
6.0%
o896
 
5.4%
s891
 
5.4%
/888
 
5.3%
r736
 
4.4%
i703
 
4.2%
Other values (64)6633
39.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)16637
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
-1299
 
7.8%
e1265
 
7.6%
t1225
 
7.4%
a1099
 
6.6%
n1002
 
6.0%
o896
 
5.4%
s891
 
5.4%
/888
 
5.3%
r736
 
4.4%
i703
 
4.2%
Other values (64)6633
39.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)16637
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
-1299
 
7.8%
e1265
 
7.6%
t1225
 
7.4%
a1099
 
6.6%
n1002
 
6.0%
o896
 
5.4%
s891
 
5.4%
/888
 
5.3%
r736
 
4.4%
i703
 
4.2%
Other values (64)6633
39.9%

info_source_4
Text

Missing 

Distinct63
Distinct (%)98.4%
Missing1196
Missing (%)94.9%
Memory size10.0 KiB
2026-01-10T17:20:19.071202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length176
Median length119.5
Mean length108.109375
Min length24

Characters and Unicode

Total characters6919
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)96.9%

Sample

1st rowhttps://www.wbrc.com/2025/09/14/bessemer-residents-frustrated-over-proposed-data-center/
2nd rowhttps://www.datacenterdynamics.com/en/news/land-developer-vermaland-plans-33bn-data-center-in-arizona/
3rd rowhttps://apnews.com/article/tucson-data-management-and-storage-arizona-general-news-environmental-conservation-42c1e554b02b4293685a08a4574db9f0
4th rowhttps://www.datacenterdynamics.com/en/news/data-center-proposed-in-twiggs-county-georgia/
5th rowhttps://epoch.ai/data/data-centers/satellite-explorer/MicrosoftFairwaterFayettevilleGeorgia?ref=404media.co
ValueCountFrequency (%)
https://rbnenergy.com/i-know-places-tech-giants-may-be-the-surest-bets-for-data-center-power-demand2
 
3.1%
https://www.datacenterdynamics.com/en/news/land-developer-vermaland-plans-33bn-data-center-in-arizona1
 
1.6%
https://www.wbrc.com/2025/09/14/bessemer-residents-frustrated-over-proposed-data-center1
 
1.6%
https://www.datacenterdynamics.com/en/news/data-center-proposed-in-twiggs-county-georgia1
 
1.6%
https://epoch.ai/data/data-centers/satellite-explorer/microsoftfairwaterfayettevillegeorgia?ref=404media.co1
 
1.6%
https://www.datacenterdynamics.com/en/news/indiana-approves-expanding-googles-fort-wayne-data-center-campus-onto-protected-wetlands-despite-local-opposition1
 
1.6%
https://apnews.com/article/tucson-data-management-and-storage-arizona-general-news-environmental-conservation-42c1e554b02b4293685a08a4574db9f01
 
1.6%
https://www.datacenterdynamics.com/en/news/no-plans-to-pursue-832m-project-maize-data-center-says-michigan-city-mayor1
 
1.6%
https://www.datacenterdynamics.com/en/news/google-gets-approval-for-data-center-campus-in-franklin-township-indiana1
 
1.6%
https://www.wndu.com/2025/10/29/proposed-12-billion-data-center-gets-unfavorable-recommendation-st-joe-county-committee1
 
1.6%
Other values (53)53
82.8%
2026-01-10T17:20:19.743139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e563
 
8.1%
-563
 
8.1%
t537
 
7.8%
a469
 
6.8%
n452
 
6.5%
s373
 
5.4%
o371
 
5.4%
/364
 
5.3%
r326
 
4.7%
c290
 
4.2%
Other values (59)2611
37.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)6919
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e563
 
8.1%
-563
 
8.1%
t537
 
7.8%
a469
 
6.8%
n452
 
6.5%
s373
 
5.4%
o371
 
5.4%
/364
 
5.3%
r326
 
4.7%
c290
 
4.2%
Other values (59)2611
37.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)6919
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e563
 
8.1%
-563
 
8.1%
t537
 
7.8%
a469
 
6.8%
n452
 
6.5%
s373
 
5.4%
o371
 
5.4%
/364
 
5.3%
r326
 
4.7%
c290
 
4.2%
Other values (59)2611
37.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)6919
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e563
 
8.1%
-563
 
8.1%
t537
 
7.8%
a469
 
6.8%
n452
 
6.5%
s373
 
5.4%
o371
 
5.4%
/364
 
5.3%
r326
 
4.7%
c290
 
4.2%
Other values (59)2611
37.7%

info_source_5
Text

Missing 

Distinct37
Distinct (%)100.0%
Missing1223
Missing (%)97.1%
Memory size10.0 KiB
2026-01-10T17:20:20.150681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length190
Median length108
Mean length106.3243243
Min length56

Characters and Unicode

Total characters3934
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st rowhttps://www.twiggscounty.us/wp-content/uploads/2025/08/Pine-Ridge-Data-Center-Facts-Sheet.pdf
2nd rowhttps://cleanview.co/public/data-centers/georgia/1896/fairwater-2---atlanta
3rd rowhttps://www.wishtv.com/news/i-team-8/google-data-center-franklin-township/
4th rowhttps://www.aboutamazon.com/news/aws/aws-project-rainier-ai-trainium-chips-compute-cluster
5th rowhttps://www.wndu.com/2025/10/23/new-carlisle-town-council-opposes-proposed-12-billion-data-center/
ValueCountFrequency (%)
https://www.twiggscounty.us/wp-content/uploads/2025/08/pine-ridge-data-center-facts-sheet.pdf1
 
2.7%
https://cleanview.co/public/data-centers/georgia/1896/fairwater-2---atlanta1
 
2.7%
https://www.wishtv.com/news/i-team-8/google-data-center-franklin-township1
 
2.7%
https://www.aboutamazon.com/news/aws/aws-project-rainier-ai-trainium-chips-compute-cluster1
 
2.7%
https://www.wndu.com/2025/10/23/new-carlisle-town-council-opposes-proposed-12-billion-data-center1
 
2.7%
https://www.datacenterdynamics.com/en/news/kentuckys-oldham-county-passes-150-day-data-center-moratorium1
 
2.7%
https://www.datacenterdynamics.com/en/news/entergy-obtains-approval-to-construct-three-gas-facilities-to-serve-metas-2gw-data-center-in-louisiana1
 
2.7%
https://www.mlive.com/news/ann-arbor/2025/11/meta-behind-1b-data-center-project-near-howell-trustee-confirms.html1
 
2.7%
https://www.mlive.com/news/ann-arbor/2025/10/rural-residents-in-an-uproar-over-openais-massive-data-center-project-in-saline-township.html1
 
2.7%
https://www.mprnews.org/story/2025/10/21/hermantown-data-center-moves-forward-despite-opposition1
 
2.7%
Other values (27)27
73.0%
2026-01-10T17:20:21.015751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e329
 
8.4%
t308
 
7.8%
-298
 
7.6%
a279
 
7.1%
n231
 
5.9%
/221
 
5.6%
s206
 
5.2%
o199
 
5.1%
i184
 
4.7%
r182
 
4.6%
Other values (48)1497
38.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)3934
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e329
 
8.4%
t308
 
7.8%
-298
 
7.6%
a279
 
7.1%
n231
 
5.9%
/221
 
5.6%
s206
 
5.2%
o199
 
5.1%
i184
 
4.7%
r182
 
4.6%
Other values (48)1497
38.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3934
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e329
 
8.4%
t308
 
7.8%
-298
 
7.6%
a279
 
7.1%
n231
 
5.9%
/221
 
5.6%
s206
 
5.2%
o199
 
5.1%
i184
 
4.7%
r182
 
4.6%
Other values (48)1497
38.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3934
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e329
 
8.4%
t308
 
7.8%
-298
 
7.6%
a279
 
7.1%
n231
 
5.9%
/221
 
5.6%
s206
 
5.2%
o199
 
5.1%
i184
 
4.7%
r182
 
4.6%
Other values (48)1497
38.1%

info_source_6
Text

Missing 

Distinct25
Distinct (%)100.0%
Missing1235
Missing (%)98.0%
Memory size10.0 KiB
2026-01-10T17:20:21.364292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length307
Median length113
Mean length129.8
Min length61

Characters and Unicode

Total characters3245
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowhttps://www.kgun9.com/news/local-news/project-blue-moves-to-build-despite-opposition
2nd rowhttps://wgxa.tv/news/local/environmental-advocate-urges-twiggs-county-to-reject-data-center-plans-near-ocmulgee-river
3rd rowhttps://www.indystar.com/story/news/local/marion-county/2025/09/22/google-withdraws-controversial-data-center-in-franklin-township-indianapolis-city-county-council/86165695007/
4th rowhttps://epoch.ai/data/data-centers/satellite-explorer/AnthropicAmazonProjectRainierNewCarlisleIndiana?ref=404media.co
5th rowhttps://wsbt.com/news/local/st-joseph-county-council-denies-rezoning-of-land-for-data-center-votes-7-2-marathon-meeting-hours-long-public-opinion-13-billion-dollar-project-amazon-new-carlisle-approval-process-plan-commission-st-joseph-county-indiana
ValueCountFrequency (%)
https://www.kgun9.com/news/local-news/project-blue-moves-to-build-despite-opposition1
 
4.0%
https://wgxa.tv/news/local/environmental-advocate-urges-twiggs-county-to-reject-data-center-plans-near-ocmulgee-river1
 
4.0%
https://www.indystar.com/story/news/local/marion-county/2025/09/22/google-withdraws-controversial-data-center-in-franklin-township-indianapolis-city-county-council/861656950071
 
4.0%
https://epoch.ai/data/data-centers/satellite-explorer/anthropicamazonprojectrainiernewcarlisleindiana?ref=404media.co1
 
4.0%
https://wsbt.com/news/local/st-joseph-county-council-denies-rezoning-of-land-for-data-center-votes-7-2-marathon-meeting-hours-long-public-opinion-13-billion-dollar-project-amazon-new-carlisle-approval-process-plan-commission-st-joseph-county-indiana1
 
4.0%
https://www.lpm.org/news/2025-06-03/oldham-county-data-center-switches-sites-reduces-size-amid-local-resistance1
 
4.0%
https://www.bgr.com/1990532/meta-new-aid-data-center-size-70-football-fields-residents-scared-water1
 
4.0%
https://www.whmi.com/news/article/developers-withdraw-re-zoning-application-for-proposed-data-center-in-howell-twp?fbclid=iwy2xjawojxd5lehrua2flbqixmabicmlketfgtwdntnfwvzhhufaxcxrrc3j0ywzhchbfawqqmjiymdm5mtc4odiwmdg5mgabhqbt42sjpesm_b2bmdynzgnbkwqqw2rx4bxuivk3lynylj84qbo_n3pdm2yp_aem_soh2yzjxxo5boquwuyebew1
 
4.0%
https://www.mlive.com/news/2025/11/dte-asks-to-rush-approval-of-massive-data-center-deal-avoiding-hearings.html1
 
4.0%
https://www.mprnews.org/story/2025/10/22/hermantown-delays-permits-for-disputed-data-center1
 
4.0%
Other values (15)15
60.0%
2026-01-10T17:20:21.970014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
-272
 
8.4%
e252
 
7.8%
t233
 
7.2%
a195
 
6.0%
n189
 
5.8%
o170
 
5.2%
s162
 
5.0%
/157
 
4.8%
i148
 
4.6%
r136
 
4.2%
Other values (61)1331
41.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)3245
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
-272
 
8.4%
e252
 
7.8%
t233
 
7.2%
a195
 
6.0%
n189
 
5.8%
o170
 
5.2%
s162
 
5.0%
/157
 
4.8%
i148
 
4.6%
r136
 
4.2%
Other values (61)1331
41.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3245
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
-272
 
8.4%
e252
 
7.8%
t233
 
7.2%
a195
 
6.0%
n189
 
5.8%
o170
 
5.2%
s162
 
5.0%
/157
 
4.8%
i148
 
4.6%
r136
 
4.2%
Other values (61)1331
41.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3245
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
-272
 
8.4%
e252
 
7.8%
t233
 
7.2%
a195
 
6.0%
n189
 
5.8%
o170
 
5.2%
s162
 
5.0%
/157
 
4.8%
i148
 
4.6%
r136
 
4.2%
Other values (61)1331
41.0%

info_source_7
Text

Missing 

Distinct11
Distinct (%)100.0%
Missing1249
Missing (%)99.1%
Memory size10.0 KiB
2026-01-10T17:20:22.344467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length145
Median length102
Mean length103.4545455
Min length66

Characters and Unicode

Total characters1138
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st rowhttps://www.41nbc.com/twiggs-county-data-center-rezoning-approval/
2nd rowhttps://lailluminator.com/briefs/entergy-builds-power-plant-for-data-center/
3rd rowhttps://www.whmi.com/news/article/vangilder-family-farm-data-center
4th rowhttps://thelivingstonpost.com/data-center-developer-takes-a-small-michigan-farming-community-to-court/
5th rowhttps://www.mprnews.org/story/2025/11/14/hermantown-data-center-developer-plans-public-meeting
ValueCountFrequency (%)
https://www.41nbc.com/twiggs-county-data-center-rezoning-approval1
9.1%
https://lailluminator.com/briefs/entergy-builds-power-plant-for-data-center1
9.1%
https://www.whmi.com/news/article/vangilder-family-farm-data-center1
9.1%
https://thelivingstonpost.com/data-center-developer-takes-a-small-michigan-farming-community-to-court1
9.1%
https://www.mprnews.org/story/2025/11/14/hermantown-data-center-developer-plans-public-meeting1
9.1%
https://www.datacenterdynamics.com/en/news/groups-sue-to-stall-data-center-project-in-do%c3%b1a-ana-county-new-mexico1
9.1%
https://www.journal-news.com/news/residents-say-no-on-1b-data-center-project-wants-hamilton-to-do-the-same/l3yusllr2vhmdfxvbxkpbtohca1
9.1%
https://www.pa.gov/agencies/dep/newsroom/2025-12-22-dep-to-host-informational-public-meeting-for-project-gravity-data-center-in-lackawanna-county1
9.1%
https://www.riotblockchain.com/news-media/press-releases/detail/127/riot-blockchain-announces-1-gw-development-in-navarro1
9.1%
https://epoch.ai/data/data-centers/satellite-explorer/microsoftfairwatermountpleasantwisconsin?ref=404media.co1
9.1%
2026-01-10T17:20:22.921689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t95
 
8.3%
-91
 
8.0%
e87
 
7.6%
a79
 
6.9%
n72
 
6.3%
o65
 
5.7%
/60
 
5.3%
r54
 
4.7%
s53
 
4.7%
c52
 
4.6%
Other values (49)430
37.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)1138
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t95
 
8.3%
-91
 
8.0%
e87
 
7.6%
a79
 
6.9%
n72
 
6.3%
o65
 
5.7%
/60
 
5.3%
r54
 
4.7%
s53
 
4.7%
c52
 
4.6%
Other values (49)430
37.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1138
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t95
 
8.3%
-91
 
8.0%
e87
 
7.6%
a79
 
6.9%
n72
 
6.3%
o65
 
5.7%
/60
 
5.3%
r54
 
4.7%
s53
 
4.7%
c52
 
4.6%
Other values (49)430
37.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1138
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t95
 
8.3%
-91
 
8.0%
e87
 
7.6%
a79
 
6.9%
n72
 
6.3%
o65
 
5.7%
/60
 
5.3%
r54
 
4.7%
s53
 
4.7%
c52
 
4.6%
Other values (49)430
37.8%

info_source_8
Text

Missing 

Distinct5
Distinct (%)100.0%
Missing1255
Missing (%)99.6%
Memory size10.0 KiB
2026-01-10T17:20:23.235153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length97
Median length80
Mean length80
Min length66

Characters and Unicode

Total characters400
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://www.41nbc.com/twiggs-county-data-center-rezoning-approval/
2nd rowhttps://planetdetroit.org/2025/12/billion-dollar-data-center-paused/
3rd rowhttps://www.wfmj.com/story/53219407/michigan-secures-new-data-center-joining-lordstown-in-ai-race
4th rowhttps://www.wvxu.org/environment/2025-12-03/developers-data-center-butler-county
5th rowhttps://paenvironmentdaily.blogspot.com/2025/12/dep-to-host-jan-6-public-information.html
ValueCountFrequency (%)
https://www.41nbc.com/twiggs-county-data-center-rezoning-approval1
20.0%
https://planetdetroit.org/2025/12/billion-dollar-data-center-paused1
20.0%
https://www.wfmj.com/story/53219407/michigan-secures-new-data-center-joining-lordstown-in-ai-race1
20.0%
https://www.wvxu.org/environment/2025-12-03/developers-data-center-butler-county1
20.0%
https://paenvironmentdaily.blogspot.com/2025/12/dep-to-host-jan-6-public-information.html1
20.0%
2026-01-10T17:20:23.754603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t34
 
8.5%
-30
 
7.5%
n26
 
6.5%
/25
 
6.2%
o25
 
6.2%
e25
 
6.2%
a20
 
5.0%
r19
 
4.8%
i17
 
4.2%
w14
 
3.5%
Other values (27)165
41.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)400
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t34
 
8.5%
-30
 
7.5%
n26
 
6.5%
/25
 
6.2%
o25
 
6.2%
e25
 
6.2%
a20
 
5.0%
r19
 
4.8%
i17
 
4.2%
w14
 
3.5%
Other values (27)165
41.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)400
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t34
 
8.5%
-30
 
7.5%
n26
 
6.5%
/25
 
6.2%
o25
 
6.2%
e25
 
6.2%
a20
 
5.0%
r19
 
4.8%
i17
 
4.2%
w14
 
3.5%
Other values (27)165
41.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)400
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t34
 
8.5%
-30
 
7.5%
n26
 
6.5%
/25
 
6.2%
o25
 
6.2%
e25
 
6.2%
a20
 
5.0%
r19
 
4.8%
i17
 
4.2%
w14
 
3.5%
Other values (27)165
41.2%

lat
Real number (ℝ)

Distinct1242
Distinct (%)98.8%
Missing3
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean37.65661471
Minimum25.88661
Maximum48.04007
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:23.951853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum25.88661
5-th percentile30.972011
Q133.95475
median38.775802
Q339.82814
95-th percentile43.37713
Maximum48.04007
Range22.15346
Interquartile range (IQR)5.87339

Descriptive statistics

Standard deviation3.842969466
Coefficient of variation (CV)0.1020529725
Kurtosis0.1157454858
Mean37.65661471
Median Absolute Deviation (MAD)2.010106
Skewness-0.2233498436
Sum47334.36469
Variance14.76841432
MonotonicityNot monotonic
2026-01-10T17:20:24.187750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.7554284
 
0.3%
33.8083993
 
0.2%
33.7558523
 
0.2%
33.7586022
 
0.2%
41.514752
 
0.2%
33.7441412
 
0.2%
39.964182
 
0.2%
34.418112
 
0.2%
29.478432
 
0.2%
32.38622
 
0.2%
Other values (1232)1233
97.9%
(Missing)3
 
0.2%
ValueCountFrequency (%)
25.886611
0.1%
26.201931
0.1%
26.24191
0.1%
26.25171
0.1%
26.323191
0.1%
ValueCountFrequency (%)
48.040071
0.1%
47.841651
0.1%
47.822661
0.1%
47.672051
0.1%
47.619011
0.1%

long
Real number (ℝ)

Distinct1236
Distinct (%)98.3%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean-85.91560952
Minimum-123.05
Maximum0
Zeros1
Zeros (%)0.1%
Negative1257
Negative (%)99.8%
Memory size10.0 KiB
2026-01-10T17:20:24.467991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-123.05
5-th percentile-112.37865
Q1-91.1256655
median-82.75155
Q3-77.47991775
95-th percentile-75.94588665
Maximum0
Range123.05
Interquartile range (IQR)13.64574775

Descriptive statistics

Standard deviation11.88786353
Coefficient of variation (CV)-0.1383667485
Kurtosis3.637190515
Mean-85.91560952
Median Absolute Deviation (MAD)5.285702
Skewness-1.157083798
Sum-108081.8368
Variance141.3212994
MonotonicityNot monotonic
2026-01-10T17:20:24.725603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-84.3914574
 
0.3%
-84.4546893
 
0.2%
-84.3910683
 
0.2%
-122.9392
 
0.2%
-122.9382
 
0.2%
-121.9532
 
0.2%
-83.01712
 
0.2%
-84.5812152
 
0.2%
-84.3878562
 
0.2%
-83.00252
 
0.2%
Other values (1226)1234
97.9%
ValueCountFrequency (%)
-123.051
0.1%
-122.9392
0.2%
-122.9382
0.2%
-122.9151
0.1%
-122.8951
0.1%
ValueCountFrequency (%)
01
0.1%
-69.6942861
0.1%
-70.2185881
0.1%
-71.07521
0.1%
-72.16731
0.1%
Distinct131
Distinct (%)10.4%
Missing3
Missing (%)0.2%
Memory size10.0 KiB
2026-01-10T17:20:25.182280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.007955449
Min length8

Characters and Unicode

Total characters11323
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)2.1%

Sample

1st row9/16/2025
2nd row8/25/2025
3rd row7/15/2025
4th row8/25/2025
5th row8/11/2025
ValueCountFrequency (%)
4/10/2024252
 
20.0%
10/16/2025114
 
9.1%
8/5/202555
 
4.4%
8/6/202539
 
3.1%
11/24/202531
 
2.5%
5/27/202528
 
2.2%
8/14/202528
 
2.2%
8/11/202526
 
2.1%
5/26/202522
 
1.8%
6/24/202522
 
1.8%
Other values (121)640
50.9%
2026-01-10T17:20:25.798957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22904
25.6%
/2514
22.2%
01690
14.9%
51226
10.8%
11154
 
10.2%
4671
 
5.9%
8391
 
3.5%
6341
 
3.0%
9196
 
1.7%
7158
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)11323
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
22904
25.6%
/2514
22.2%
01690
14.9%
51226
10.8%
11154
 
10.2%
4671
 
5.9%
8391
 
3.5%
6341
 
3.0%
9196
 
1.7%
7158
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)11323
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
22904
25.6%
/2514
22.2%
01690
14.9%
51226
10.8%
11154
 
10.2%
4671
 
5.9%
8391
 
3.5%
6341
 
3.0%
9196
 
1.7%
7158
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)11323
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
22904
25.6%
/2514
22.2%
01690
14.9%
51226
10.8%
11154
 
10.2%
4671
 
5.9%
8391
 
3.5%
6341
 
3.0%
9196
 
1.7%
7158
 
1.4%

date_updated
Text

Missing 

Distinct113
Distinct (%)9.8%
Missing102
Missing (%)8.1%
Memory size10.0 KiB
2026-01-10T17:20:26.159456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.377374784
Min length8

Characters and Unicode

Total characters10859
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)2.7%

Sample

1st row9/16/2025
2nd row8/25/2025
3rd row7/15/2025
4th row8/25/2025
5th row8/11/2025
ValueCountFrequency (%)
10/17/2025389
33.6%
10/16/2025112
 
9.7%
8/5/202553
 
4.6%
11/24/202532
 
2.8%
8/14/202527
 
2.3%
5/27/202526
 
2.2%
6/24/202521
 
1.8%
6/19/202520
 
1.7%
5/26/202519
 
1.6%
8/30/202518
 
1.6%
Other values (103)441
38.1%
2026-01-10T17:20:26.725094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22638
24.3%
/2316
21.3%
01718
15.8%
11476
13.6%
51374
12.7%
7473
 
4.4%
6264
 
2.4%
8242
 
2.2%
9165
 
1.5%
4116
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)10859
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
22638
24.3%
/2316
21.3%
01718
15.8%
11476
13.6%
51374
12.7%
7473
 
4.4%
6264
 
2.4%
8242
 
2.2%
9165
 
1.5%
4116
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)10859
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
22638
24.3%
/2316
21.3%
01718
15.8%
11476
13.6%
51374
12.7%
7473
 
4.4%
6264
 
2.4%
8242
 
2.2%
9165
 
1.5%
4116
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)10859
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
22638
24.3%
/2316
21.3%
01718
15.8%
11476
13.6%
51374
12.7%
7473
 
4.4%
6264
 
2.4%
8242
 
2.2%
9165
 
1.5%
4116
 
1.1%

mw_high
Text

Missing 

Distinct148
Distinct (%)36.7%
Missing857
Missing (%)68.0%
Memory size10.0 KiB
2026-01-10T17:20:27.213001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length6
Mean length2.722084367
Min length1

Characters and Unicode

Total characters1097
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)20.8%

Sample

1st row1,200
2nd row210
3rd row32
4th row200
5th row160
ValueCountFrequency (%)
219
 
4.7%
20017
 
4.2%
30016
 
4.0%
1,00013
 
3.2%
413
 
3.2%
60012
 
3.0%
10010
 
2.5%
109
 
2.2%
128
 
2.0%
1,5007
 
1.7%
Other values (137)279
69.2%
2026-01-10T17:20:27.949702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0382
34.8%
1140
 
12.8%
2126
 
11.5%
376
 
6.9%
476
 
6.9%
571
 
6.5%
,65
 
5.9%
655
 
5.0%
848
 
4.4%
735
 
3.2%
Other values (3)23
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1097
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0382
34.8%
1140
 
12.8%
2126
 
11.5%
376
 
6.9%
476
 
6.9%
571
 
6.5%
,65
 
5.9%
655
 
5.0%
848
 
4.4%
735
 
3.2%
Other values (3)23
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1097
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0382
34.8%
1140
 
12.8%
2126
 
11.5%
376
 
6.9%
476
 
6.9%
571
 
6.5%
,65
 
5.9%
655
 
5.0%
848
 
4.4%
735
 
3.2%
Other values (3)23
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1097
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0382
34.8%
1140
 
12.8%
2126
 
11.5%
376
 
6.9%
476
 
6.9%
571
 
6.5%
,65
 
5.9%
655
 
5.0%
848
 
4.4%
735
 
3.2%
Other values (3)23
 
2.1%
Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:28.131832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length7
Mean length11.55238095
Min length7

Characters and Unicode

Total characters14556
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMega campus (>1,000 MW)
2nd rowUnknown
3rd rowUnknown
4th rowUnknown
5th rowUnknown
ValueCountFrequency (%)
unknown820
37.2%
mw440
20.0%
hyperscale187
 
8.5%
101-999187
 
8.5%
small82
 
3.7%
0-1082
 
3.7%
medium82
 
3.7%
11-5082
 
3.7%
mega63
 
2.9%
campus63
 
2.9%
Other values (3)115
 
5.2%
2026-01-10T17:20:28.475716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n2460
16.9%
943
 
6.5%
U820
 
5.6%
o820
 
5.6%
k820
 
5.6%
w820
 
5.6%
1735
 
5.0%
0674
 
4.6%
M585
 
4.0%
9561
 
3.9%
Other values (23)5318
36.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)14556
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n2460
16.9%
943
 
6.5%
U820
 
5.6%
o820
 
5.6%
k820
 
5.6%
w820
 
5.6%
1735
 
5.0%
0674
 
4.6%
M585
 
4.0%
9561
 
3.9%
Other values (23)5318
36.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)14556
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n2460
16.9%
943
 
6.5%
U820
 
5.6%
o820
 
5.6%
k820
 
5.6%
w820
 
5.6%
1735
 
5.0%
0674
 
4.6%
M585
 
4.0%
9561
 
3.9%
Other values (23)5318
36.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)14556
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n2460
16.9%
943
 
6.5%
U820
 
5.6%
o820
 
5.6%
k820
 
5.6%
w820
 
5.6%
1735
 
5.0%
0674
 
4.6%
M585
 
4.0%
9561
 
3.9%
Other values (23)5318
36.5%

sizerank_numeric
Real number (ℝ)

Distinct6
Distinct (%)0.5%
Missing3
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean2.098647574
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:28.604411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.709324302
Coefficient of variation (CV)0.8144884944
Kurtosis-0.2696231644
Mean2.098647574
Median Absolute Deviation (MAD)0
Skewness1.182650256
Sum2638
Variance2.921789571
MonotonicityNot monotonic
2026-01-10T17:20:28.738647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1819
65.0%
5187
 
14.8%
282
 
6.5%
380
 
6.3%
662
 
4.9%
427
 
2.1%
(Missing)3
 
0.2%
ValueCountFrequency (%)
1819
65.0%
282
 
6.5%
380
 
6.3%
427
 
2.1%
5187
 
14.8%
ValueCountFrequency (%)
662
 
4.9%
5187
14.8%
427
 
2.1%
380
6.3%
282
6.5%

power_source
Text

Missing 

Distinct7
Distinct (%)23.3%
Missing1230
Missing (%)97.6%
Memory size10.0 KiB
2026-01-10T17:20:28.953394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length24
Mean length15.43333333
Min length5

Characters and Unicode

Total characters463
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st rowHydroelectric
2nd rowNuclear
3rd rowSolar
4th rowNatural gas
5th rowGrid (unspecified mix)
ValueCountFrequency (%)
natural13
18.6%
gas13
18.6%
grid12
17.1%
unspecified11
15.7%
mix11
15.7%
nuclear3
 
4.3%
solar1
 
1.4%
hydroelectric1
 
1.4%
hybrid1
 
1.4%
onsite1
 
1.4%
Other values (3)3
 
4.3%
2026-01-10T17:20:29.339063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i49
 
10.6%
a46
 
9.9%
40
 
8.6%
r32
 
6.9%
e28
 
6.0%
s27
 
5.8%
u27
 
5.8%
d26
 
5.6%
l19
 
4.1%
c16
 
3.5%
Other values (19)153
33.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i49
 
10.6%
a46
 
9.9%
40
 
8.6%
r32
 
6.9%
e28
 
6.0%
s27
 
5.8%
u27
 
5.8%
d26
 
5.6%
l19
 
4.1%
c16
 
3.5%
Other values (19)153
33.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i49
 
10.6%
a46
 
9.9%
40
 
8.6%
r32
 
6.9%
e28
 
6.0%
s27
 
5.8%
u27
 
5.8%
d26
 
5.6%
l19
 
4.1%
c16
 
3.5%
Other values (19)153
33.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i49
 
10.6%
a46
 
9.9%
40
 
8.6%
r32
 
6.9%
e28
 
6.0%
s27
 
5.8%
u27
 
5.8%
d26
 
5.6%
l19
 
4.1%
c16
 
3.5%
Other values (19)153
33.0%

dedicated_power_plant
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing1259
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean2
Minimum2
Maximum2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:29.465626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median2
Q32
95-th percentile2
Maximum2
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean2
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variancenan
MonotonicityStrictly increasing
2026-01-10T17:20:29.605678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
21
 
0.1%
(Missing)1259
99.9%
ValueCountFrequency (%)
21
0.1%
ValueCountFrequency (%)
21
0.1%

number_of_generators
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing1259
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:29.751455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean0
Median Absolute Deviation (MAD)0
Skewnessnan
Sum0
Variancenan
MonotonicityStrictly increasing
2026-01-10T17:20:29.894430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
01
 
0.1%
(Missing)1259
99.9%
ValueCountFrequency (%)
01
0.1%
ValueCountFrequency (%)
01
0.1%

number_of_buildings
Text

Missing 

Distinct24
Distinct (%)31.2%
Missing1183
Missing (%)93.9%
Memory size10.0 KiB
2026-01-10T17:20:30.105667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length16
Median length1
Mean length1.623376623
Min length1

Characters and Unicode

Total characters125
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)13.0%

Sample

1st row18
2nd row5
3rd row6
4th row12
5th row7
ValueCountFrequency (%)
611
13.8%
310
12.5%
29
11.2%
49
11.2%
125
 
6.2%
55
 
6.2%
74
 
5.0%
93
 
3.8%
153
 
3.8%
103
 
3.8%
Other values (13)18
22.5%
2026-01-10T17:20:30.528069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
16.0%
215
12.0%
315
12.0%
412
9.6%
611
8.8%
59
 
7.2%
06
 
4.8%
75
 
4.0%
l5
 
4.0%
94
 
3.2%
Other values (16)23
18.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)125
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
120
16.0%
215
12.0%
315
12.0%
412
9.6%
611
8.8%
59
 
7.2%
06
 
4.8%
75
 
4.0%
l5
 
4.0%
94
 
3.2%
Other values (16)23
18.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)125
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
120
16.0%
215
12.0%
315
12.0%
412
9.6%
611
8.8%
59
 
7.2%
06
 
4.8%
75
 
4.0%
l5
 
4.0%
94
 
3.2%
Other values (16)23
18.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)125
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
120
16.0%
215
12.0%
315
12.0%
412
9.6%
611
8.8%
59
 
7.2%
06
 
4.8%
75
 
4.0%
l5
 
4.0%
94
 
3.2%
Other values (16)23
18.4%

cooling_source
Text

Missing 

Distinct3
Distinct (%)15.8%
Missing1241
Missing (%)98.5%
Memory size10.0 KiB
2026-01-10T17:20:30.690444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length16
Median length5
Mean length4.736842105
Min length3

Characters and Unicode

Total characters90
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)5.3%

Sample

1st rowWater
2nd rowWater
3rd rowAir
4th rowAir
5th rowAir
ValueCountFrequency (%)
water10
50.0%
air8
40.0%
hybrid1
 
5.0%
air/water1
 
5.0%
2026-01-10T17:20:31.038640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r21
23.3%
a12
13.3%
e11
12.2%
t11
12.2%
W10
11.1%
i10
11.1%
A8
 
8.9%
H1
 
1.1%
y1
 
1.1%
b1
 
1.1%
Other values (4)4
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)90
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r21
23.3%
a12
13.3%
e11
12.2%
t11
12.2%
W10
11.1%
i10
11.1%
A8
 
8.9%
H1
 
1.1%
y1
 
1.1%
b1
 
1.1%
Other values (4)4
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)90
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r21
23.3%
a12
13.3%
e11
12.2%
t11
12.2%
W10
11.1%
i10
11.1%
A8
 
8.9%
H1
 
1.1%
y1
 
1.1%
b1
 
1.1%
Other values (4)4
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)90
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r21
23.3%
a12
13.3%
e11
12.2%
t11
12.2%
W10
11.1%
i10
11.1%
A8
 
8.9%
H1
 
1.1%
y1
 
1.1%
b1
 
1.1%
Other values (4)4
 
4.4%

facility_size_sq_ft
Text

Missing 

Distinct584
Distinct (%)74.3%
Missing474
Missing (%)37.6%
Memory size10.0 KiB
2026-01-10T17:20:31.440447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.421119593
Min length2

Characters and Unicode

Total characters5833
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique499 ?
Unique (%)63.5%

Sample

1st row4,500,000
2nd row270,000
3rd row715,000
4th row2,160,000
5th row34,623
ValueCountFrequency (%)
1,000,00021
 
2.7%
1,800,00011
 
1.4%
1,500,0009
 
1.1%
2,100,0008
 
1.0%
2,200,0008
 
1.0%
1,600,0007
 
0.9%
1,300,0006
 
0.8%
250,0006
 
0.8%
1,200,0006
 
0.8%
180,0006
 
0.8%
Other values (574)698
88.8%
2026-01-10T17:20:32.036988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
02217
38.0%
,1024
17.6%
1445
 
7.6%
2392
 
6.7%
5326
 
5.6%
3288
 
4.9%
4277
 
4.7%
6241
 
4.1%
8237
 
4.1%
7217
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)5833
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
02217
38.0%
,1024
17.6%
1445
 
7.6%
2392
 
6.7%
5326
 
5.6%
3288
 
4.9%
4277
 
4.7%
6241
 
4.1%
8237
 
4.1%
7217
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)5833
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
02217
38.0%
,1024
17.6%
1445
 
7.6%
2392
 
6.7%
5326
 
5.6%
3288
 
4.9%
4277
 
4.7%
6241
 
4.1%
8237
 
4.1%
7217
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)5833
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
02217
38.0%
,1024
17.6%
1445
 
7.6%
2392
 
6.7%
5326
 
5.6%
3288
 
4.9%
4277
 
4.7%
6241
 
4.1%
8237
 
4.1%
7217
 
3.7%

cooling_type
Text

Missing 

Distinct3
Distinct (%)18.8%
Missing1244
Missing (%)98.7%
Memory size10.0 KiB
2026-01-10T17:20:32.219719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.3125
Min length4

Characters and Unicode

Total characters165
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)6.2%

Sample

1st rowClosed loop
2nd rowClosed loop
3rd rowClosed loop
4th rowClosed loop
5th rowClosed loop
ValueCountFrequency (%)
loop15
48.4%
closed13
41.9%
open2
 
6.5%
fans1
 
3.2%
2026-01-10T17:20:32.569994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o43
26.1%
l28
17.0%
p17
 
10.3%
e15
 
9.1%
15
 
9.1%
s14
 
8.5%
C13
 
7.9%
d13
 
7.9%
n3
 
1.8%
O2
 
1.2%
Other values (2)2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)165
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o43
26.1%
l28
17.0%
p17
 
10.3%
e15
 
9.1%
15
 
9.1%
s14
 
8.5%
C13
 
7.9%
d13
 
7.9%
n3
 
1.8%
O2
 
1.2%
Other values (2)2
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)165
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o43
26.1%
l28
17.0%
p17
 
10.3%
e15
 
9.1%
15
 
9.1%
s14
 
8.5%
C13
 
7.9%
d13
 
7.9%
n3
 
1.8%
O2
 
1.2%
Other values (2)2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)165
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o43
26.1%
l28
17.0%
p17
 
10.3%
e15
 
9.1%
15
 
9.1%
s14
 
8.5%
C13
 
7.9%
d13
 
7.9%
n3
 
1.8%
O2
 
1.2%
Other values (2)2
 
1.2%

property_size_acres
Text

Missing 

Distinct309
Distinct (%)45.1%
Missing575
Missing (%)45.6%
Memory size10.0 KiB
2026-01-10T17:20:33.168537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length8
Mean length2.551824818
Min length1

Characters and Unicode

Total characters1748
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)26.3%

Sample

1st row675
2nd row360
3rd row135
4th row920
5th row66
ValueCountFrequency (%)
1020
 
2.9%
1115
 
2.2%
614
 
2.0%
1414
 
2.0%
1713
 
1.9%
1212
 
1.8%
812
 
1.8%
911
 
1.6%
1610
 
1.5%
79
 
1.3%
Other values (297)555
81.0%
2026-01-10T17:20:34.012488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1329
18.8%
0287
16.4%
2212
12.1%
3168
9.6%
5152
8.7%
4142
8.1%
6117
 
6.7%
8102
 
5.8%
791
 
5.2%
988
 
5.0%
Other values (4)60
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)1748
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1329
18.8%
0287
16.4%
2212
12.1%
3168
9.6%
5152
8.7%
4142
8.1%
6117
 
6.7%
8102
 
5.8%
791
 
5.2%
988
 
5.0%
Other values (4)60
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1748
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1329
18.8%
0287
16.4%
2212
12.1%
3168
9.6%
5152
8.7%
4142
8.1%
6117
 
6.7%
8102
 
5.8%
791
 
5.2%
988
 
5.0%
Other values (4)60
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1748
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1329
18.8%
0287
16.4%
2212
12.1%
3168
9.6%
5152
8.7%
4142
8.1%
6117
 
6.7%
8102
 
5.8%
791
 
5.2%
988
 
5.0%
Other values (4)60
 
3.4%

project_cost
Text

Missing 

Distinct99
Distinct (%)57.6%
Missing1088
Missing (%)86.3%
Memory size10.0 KiB
2026-01-10T17:20:34.392821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length15
Mean length11.55813953
Min length10

Characters and Unicode

Total characters1988
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)43.0%

Sample

1st row$600 million
2nd row$800 million
3rd row$8 billion
4th row$1 billion
5th row$10 billion
ValueCountFrequency (%)
billion98
28.3%
million73
21.1%
120
 
5.8%
108
 
2.3%
8007
 
2.0%
67
 
2.0%
37
 
2.0%
55
 
1.4%
1.25
 
1.4%
5005
 
1.4%
Other values (86)111
32.1%
2026-01-10T17:20:34.949379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i347
17.5%
l346
17.4%
175
8.8%
$174
8.8%
n173
8.7%
o173
8.7%
b98
 
4.9%
179
 
4.0%
076
 
3.8%
m75
 
3.8%
Other values (12)272
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)1988
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i347
17.5%
l346
17.4%
175
8.8%
$174
8.8%
n173
8.7%
o173
8.7%
b98
 
4.9%
179
 
4.0%
076
 
3.8%
m75
 
3.8%
Other values (12)272
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1988
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i347
17.5%
l346
17.4%
175
8.8%
$174
8.8%
n173
8.7%
o173
8.7%
b98
 
4.9%
179
 
4.0%
076
 
3.8%
m75
 
3.8%
Other values (12)272
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1988
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i347
17.5%
l346
17.4%
175
8.8%
$174
8.8%
n173
8.7%
o173
8.7%
b98
 
4.9%
179
 
4.0%
076
 
3.8%
m75
 
3.8%
Other values (12)272
13.7%

other_info
Text

Missing 

Distinct271
Distinct (%)59.8%
Missing807
Missing (%)64.0%
Memory size10.0 KiB
2026-01-10T17:20:35.479773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length416
Median length266
Mean length62.67108168
Min length4

Characters and Unicode

Total characters28390
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)55.4%

Sample

1st row100 acres to be cleared
2nd rowPower from Glen Canyon Dam
3rd rowRunning on hydrogen fuel
4th rowLiquid cooled
5th rowLiquid cooled
ValueCountFrequency (%)
the213
 
4.9%
acreage130
 
3.0%
project110
 
2.5%
center102
 
2.4%
to92
 
2.1%
covers90
 
2.1%
of69
 
1.6%
has59
 
1.4%
this59
 
1.4%
computer58
 
1.3%
Other values (1067)3336
77.3%
2026-01-10T17:20:36.334076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3871
13.6%
e3292
 
11.6%
t1888
 
6.7%
r1834
 
6.5%
a1789
 
6.3%
o1759
 
6.2%
n1535
 
5.4%
s1277
 
4.5%
i1182
 
4.2%
c969
 
3.4%
Other values (73)8994
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)28390
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3871
13.6%
e3292
 
11.6%
t1888
 
6.7%
r1834
 
6.5%
a1789
 
6.3%
o1759
 
6.2%
n1535
 
5.4%
s1277
 
4.5%
i1182
 
4.2%
c969
 
3.4%
Other values (73)8994
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)28390
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3871
13.6%
e3292
 
11.6%
t1888
 
6.7%
r1834
 
6.5%
a1789
 
6.3%
o1759
 
6.2%
n1535
 
5.4%
s1277
 
4.5%
i1182
 
4.2%
c969
 
3.4%
Other values (73)8994
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)28390
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3871
13.6%
e3292
 
11.6%
t1888
 
6.7%
r1834
 
6.5%
a1789
 
6.3%
o1759
 
6.2%
n1535
 
5.4%
s1277
 
4.5%
i1182
 
4.2%
c969
 
3.4%
Other values (73)8994
31.7%

status
Text

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2026-01-10T17:20:36.547691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length37
Median length9
Mean length10.28095238
Min length7

Characters and Unicode

Total characters12954
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowProposed
2nd rowOperating
3rd rowUnknown
4th rowOperating
5th rowOperating
ValueCountFrequency (%)
proposed508
37.8%
operating494
36.8%
unknown115
 
8.6%
approved/permitted/under84
 
6.2%
construction84
 
6.2%
suspended42
 
3.1%
cancelled17
 
1.3%
2026-01-10T17:20:36.905393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e1456
11.2%
o1383
10.7%
r1338
10.3%
p1212
9.4%
n1150
8.9%
d861
 
6.6%
t830
 
6.4%
i662
 
5.1%
s634
 
4.9%
P592
 
4.6%
Other values (16)2836
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)12954
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e1456
11.2%
o1383
10.7%
r1338
10.3%
p1212
9.4%
n1150
8.9%
d861
 
6.6%
t830
 
6.4%
i662
 
5.1%
s634
 
4.9%
P592
 
4.6%
Other values (16)2836
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)12954
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e1456
11.2%
o1383
10.7%
r1338
10.3%
p1212
9.4%
n1150
8.9%
d861
 
6.6%
t830
 
6.4%
i662
 
5.1%
s634
 
4.9%
P592
 
4.6%
Other values (16)2836
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)12954
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e1456
11.2%
o1383
10.7%
r1338
10.3%
p1212
9.4%
n1150
8.9%
d861
 
6.6%
t830
 
6.4%
i662
 
5.1%
s634
 
4.9%
P592
 
4.6%
Other values (16)2836
21.9%

status_detail
Text

Missing 

Distinct5
Distinct (%)8.1%
Missing1198
Missing (%)95.1%
Memory size10.0 KiB
2026-01-10T17:20:37.130256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length116
Median length9
Mean length12.35483871
Min length9

Characters and Unicode

Total characters766
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st rowExpansion
2nd rowExpanding
3rd rowExpanding
4th rowExpanding
5th rowExpanding
ValueCountFrequency (%)
expansion32
39.0%
redevelopment25
30.5%
expanding5
 
6.1%
on2
 
2.4%
construction1
 
1.2%
with1
 
1.2%
started1
 
1.2%
a1
 
1.2%
20,0001
 
1.2%
sq1
 
1.2%
Other values (12)12
 
14.6%
2026-01-10T17:20:37.519264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n105
13.7%
e104
13.6%
p63
 
8.2%
o62
 
8.1%
a47
 
6.1%
i43
 
5.6%
E37
 
4.8%
x37
 
4.8%
s36
 
4.7%
t36
 
4.7%
Other values (22)196
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)766
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n105
13.7%
e104
13.6%
p63
 
8.2%
o62
 
8.1%
a47
 
6.1%
i43
 
5.6%
E37
 
4.8%
x37
 
4.8%
s36
 
4.7%
t36
 
4.7%
Other values (22)196
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)766
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n105
13.7%
e104
13.6%
p63
 
8.2%
o62
 
8.1%
a47
 
6.1%
i43
 
5.6%
E37
 
4.8%
x37
 
4.8%
s36
 
4.7%
t36
 
4.7%
Other values (22)196
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)766
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n105
13.7%
e104
13.6%
p63
 
8.2%
o62
 
8.1%
a47
 
6.1%
i43
 
5.6%
E37
 
4.8%
x37
 
4.8%
s36
 
4.7%
t36
 
4.7%
Other values (22)196
25.6%

expected_date_online
Text

Missing 

Distinct9
Distinct (%)25.0%
Missing1224
Missing (%)97.1%
Memory size10.0 KiB
2026-01-10T17:20:37.707291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length21
Median length4
Mean length4.555555556
Min length4

Characters and Unicode

Total characters164
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)8.3%

Sample

1st row2026
2nd rowFull buildout by 2037
3rd row2027
4th row2027
5th row2027
ValueCountFrequency (%)
202711
28.2%
20268
20.5%
20287
17.9%
20253
 
7.7%
20292
 
5.1%
20302
 
5.1%
full1
 
2.6%
buildout1
 
2.6%
by1
 
2.6%
20371
 
2.6%
Other values (2)2
 
5.1%
2026-01-10T17:20:38.101512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
42.7%
038
23.2%
713
 
7.9%
68
 
4.9%
88
 
4.9%
53
 
1.8%
33
 
1.8%
u3
 
1.8%
3
 
1.8%
l3
 
1.8%
Other values (10)12
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)164
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
270
42.7%
038
23.2%
713
 
7.9%
68
 
4.9%
88
 
4.9%
53
 
1.8%
33
 
1.8%
u3
 
1.8%
3
 
1.8%
l3
 
1.8%
Other values (10)12
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)164
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
270
42.7%
038
23.2%
713
 
7.9%
68
 
4.9%
88
 
4.9%
53
 
1.8%
33
 
1.8%
u3
 
1.8%
3
 
1.8%
l3
 
1.8%
Other values (10)12
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)164
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
270
42.7%
038
23.2%
713
 
7.9%
68
 
4.9%
88
 
4.9%
53
 
1.8%
33
 
1.8%
u3
 
1.8%
3
 
1.8%
l3
 
1.8%
Other values (10)12
 
7.3%

county
Text

Missing 

Distinct103
Distinct (%)21.1%
Missing771
Missing (%)61.2%
Memory size10.0 KiB
2026-01-10T17:20:38.539912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.206543967
Min length4

Characters and Unicode

Total characters4013
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)13.3%

Sample

1st rowSt Lucie
2nd rowPalm Beach
3rd rowFloyd
4th rowBartow
5th rowFulton
ValueCountFrequency (%)
loudoun147
25.3%
prince73
12.6%
william72
12.4%
fulton53
 
9.1%
fairfax27
 
4.6%
douglas17
 
2.9%
henrico12
 
2.1%
county11
 
1.9%
fauquier10
 
1.7%
gwinnett6
 
1.0%
Other values (100)153
26.3%
2026-01-10T17:20:39.181447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o474
11.8%
u418
 
10.4%
n378
 
9.4%
i317
 
7.9%
l285
 
7.1%
a242
 
6.0%
e218
 
5.4%
r187
 
4.7%
d171
 
4.3%
L157
 
3.9%
Other values (39)1166
29.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)4013
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o474
11.8%
u418
 
10.4%
n378
 
9.4%
i317
 
7.9%
l285
 
7.1%
a242
 
6.0%
e218
 
5.4%
r187
 
4.7%
d171
 
4.3%
L157
 
3.9%
Other values (39)1166
29.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4013
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o474
11.8%
u418
 
10.4%
n378
 
9.4%
i317
 
7.9%
l285
 
7.1%
a242
 
6.0%
e218
 
5.4%
r187
 
4.7%
d171
 
4.3%
L157
 
3.9%
Other values (39)1166
29.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4013
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o474
11.8%
u418
 
10.4%
n378
 
9.4%
i317
 
7.9%
l285
 
7.1%
a242
 
6.0%
e218
 
5.4%
r187
 
4.7%
d171
 
4.3%
L157
 
3.9%
Other values (39)1166
29.1%